A novel synthetic aperture radar scattering model for sea surface with breaking waves

Xiaochen Wang; Yuxin Hu; Bing Han; Wei Tian; Chunhua Zhang

doi:10.1007/s13131-021-1842-y

Volume 41 Issue 4

Apr. 2022

Turn off MathJax

Article Contents

Article Navigation > Acta Oceanologica Sinica > 2022 > 41(4): 138-145

Xiaochen Wang, Yuxin Hu, Bing Han, Wei Tian, Chunhua Zhang. A novel synthetic aperture radar scattering model for sea surface with breaking waves[J]. Acta Oceanologica Sinica, 2022, 41(4): 138-145. doi: 10.1007/s13131-021-1842-y

Citation:

Xiaochen Wang, Yuxin Hu, Bing Han, Wei Tian, Chunhua Zhang. A novel synthetic aperture radar scattering model for sea surface with breaking waves[J]. Acta Oceanologica Sinica, 2022, 41(4): 138-145. doi: 10.1007/s13131-021-1842-y

Citation:

PDF( 1368 KB)

A novel synthetic aperture radar scattering model for sea surface with breaking waves

doi: 10.1007/s13131-021-1842-y

Xiaochen Wang^{1, 2},
Yuxin Hu^{1, 2
,
,},
Bing Han^{1, 2},
Wei Tian¹,
Chunhua Zhang³

1.
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
2.
Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China
3.
The box 51111, Beijing 100190, China

Funds: The National Natural Science Foundation of China under contract No. 4197060692.

More Information

Corresponding author: E-mail: huyx@aircas.ac.cn
Received Date: 2020-11-14
Accepted Date: 2021-04-14

Available Online: 2022-02-23

Publish Date: 2022-04-01

Abstract

Abstract

In this study a novel synthetic aperture radar (SAR) scattering model for sea surface with breaking waves is proposed. Compared with existing models, the proposed model considers an empirical relationship between wind speed and wave breaking scattering to present the contribution of wave breaking. Moreover, the scattering weight factor p, and wave breaking rate q, are performed to present the contribution of the quasi-specular scattering term, Bragg scattering term, and wave breaking scattering term to the total scattering from the sea surface. To explore the modeling accuracy of sea-surface scattering, a simulated normalized radar cross-section (NRCS) and measured NRCS are compared. The proposed model generated the simulated NRCS and a matching GF-3 dataset was used for the measured NRCS. It was revealed that the performance of the VV polarization of our model was much better than that of HH polarization, with a correlation of 0.91, bias of −0.14 dB, root mean square error (RMSE) of 1.26 dB, and scattering index (SI) of −0.11. In addition, the novel model is explored and compared with the geophysical model of CMODs and satellite-measured NRCS from GF-3 SAR wave mode imagery. For an incidence angle 40°–41°, the relationship between the NRCS and wind speed, relative wind direction is proposed. As with the SAR-measured NRCS, the performance of VV polarization was much better than HH polarization, with a correlation of 0.99, bias of −0.25 dB, RMSE of 0.64 dB, and SI of −0.04.
- synthetic aperture radar,
- scattering model,
- sea surface,
- wave breaking

FullText(HTML)

References(41)

References

[1]	Apel J R. 1994. An improved model of the ocean surface wave vector spectrum and its effects on radar backscatter. Journal of Geophysical Research: Oceans, 99(C8): 16269–16291. doi: 10.1029/94JC00846
[2]	Barrick D E. 1965. A more exact theory of backscattering from statistically rough surfaces. Columbus, Ohio: The Ohio State University Research Foundation
[3]	Barrick D, Bahar E. 1981. Rough surface scattering using specular point theory. IEEE Transactions on Antennas & Propagation, 29(5): 798–800
[4]	Chubb S R, Cooper A L, Jansen R W, et al. 1999. Radar backscatter from breaking waves in Gulf Stream current convergence fronts. IEEE Transactions on Geoscience and Remote Sensing, 37(4): 1951–1966. doi: 10.1109/36.774707
[5]	Churyumov A N, Kravtsov Y A. 2000. Microwave backscatter from mesoscale breaking waves on the sea surface. Waves in Random Media, 10(1): 1–15. doi: 10.1088/0959-7174/10/1/301
[6]	Donelan M A, Pierson W J Jr. 1987. Radar scattering and equilibrium ranges in wind-generated waves with application to scatterometry. Journal of Geophysical Research: Oceans, 92(C5): 4971–5029. doi: 10.1029/JC092iC05p04971
[7]	Elfouhaily T, Chapron B, Katsaros K, et al. 1997. A unified directional spectrum for long and short wind-driven waves. Journal of Geophysical Research: Oceans, 102(C7): 15781–15796. doi: 10.1029/97JC00467
[8]	Gao Dong, Liu Yongxin, Meng Junmin, et al. 2018. Estimating significant wave height from SAR imagery based on an SVM regression model. Acta Oceanologica Sinica, 37(3): 103–110. doi: 10.1007/s13131-018-1203-7
[9]	Hauser D, Caudal G. 1995. Behavior of the ocean radar cross-section at low incidence, observed in the vicinity of the Gulf Stream. IEEE Transactions on Geoscience and Remote Sensing, 33(1): 162–171. doi: 10.1109/36.368212
[10]	Hauser D, Caudal G. 1996. Combined analysis of the radar cross-section modulation due to the long ocean waves around 14° and 34° incidence: Implication for the hydrodynamic modulation. Journal of Geophysical Research: Oceans, 101(C11): 25833–25846. doi: 10.1029/96JC02124
[11]	Hauser D, Caudal G, Guimbard S, et al. 2008. A study of the slope probability density function of the ocean waves from radar observations. Journal of Geophysical Research: Oceans, 113(C2): C02006
[12]	Helluy P, Golay F, Caltagirone J P, et al. 2005. Numerical simulations of wave breaking. ESAIM: Mathematical Modelling and Numerical Analysis, 39(3): 591–607. doi: 10.1051/m2an:2005024
[13]	Hwang P A, Plant W J. 2010. An analysis of the effects of swell and surface roughness spectra on microwave backscatter from the ocean. Journal of Geophysical Research: Oceans, 115(C4): C04014
[14]	Hwang P A, Zhang Biao, Toporkov J V, et al. 2010. Comparison of composite Bragg theory and quad-polarization radar backscatter from RADARSAT-2: With applications to wave breaking and high wind retrieval. Journal of Geophysical Research: Oceans, 115(C8): C08019
[15]	Kudryavtsev V, Akimov D, Johannessen J, et al. 2005. On radar imaging of current features: 1. Model and comparison with observations. Journal of Geophysical Research: Oceans, 110(C7): C07016
[16]	Kudryavtsev V N, Fan Shengren, Zhang Biao, et al. 2019. On quad-polarized SAR measurements of the ocean surface. IEEE Transactions on Geoscience and Remote Sensing, 57(11): 8362–8370. doi: 10.1109/TGRS.2019.2920750
[17]	Kudryavtsev V, Hauser D, Caudal G, et al. 2003. A semiempirical model of the normalized radar cross-section of the sea surface 1. Background model. Journal of Geophysical Research: Oceans, 108(C3): FET 2-1–FET 2-24
[18]	Kudryavtsev V, Kozlov I, Chapron B, et al. 2014. Quad-polarization SAR features of ocean currents. Journal of Geophysical Research: Oceans, 119(9): 6046–6065. doi: 10.1002/2014JC010173
[19]	Li Huimin, Mouche A, Stopa J E. 2019a. Impact of sea state on wind retrieval from Sentinel-1 wave mode data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(2): 559–566. doi: 10.1109/JSTARS.2019.2893890
[20]	Li Huimin, Mouche A, Stopa J E, et al. 2019b. Calibration of the normalized radar cross section for Sentinel-1 wave mode. IEEE Transactions on Geoscience and Remote Sensing, 57(3): 1514–1522. doi: 10.1109/TGRS.2018.2867035
[21]	Mouche A A, Chapron B, Reul N, et al. 2007. Importance of the sea surface curvature to interpret the normalized radar cross section. Journal of Geophysical Research: Oceans, 112(C10): C10002. doi: 10.1029/2006JC004010
[22]	Mouche A A, Chapron B, Zhang Biao, et al. 2017. Combined co- and cross-polarized SAR measurements under extreme wind conditions. IEEE Transactions on Geoscience and Remote Sensing, 55(12): 6746–6755. doi: 10.1109/TGRS.2017.2732508
[23]	Mouche A A, Hauser D, Kudryavtsev V. 2006. Radar scattering of the ocean surface and sea-roughness properties: A combined analysis from dual-polarizations airborne radar observations and models in C band. Journal of Geophysical Research: Oceans, 111(C9): C09004
[24]	Phillips O M. 1988. Radar returns from the sea surface—Bragg scattering and breaking waves. Journal of Physical Oceanography, 18(8): 1065–1074. doi: 10.1175/1520-0485(1988)018<1065:RRFTSS>2.0.CO;2
[25]	Plant W J. 1986. A two-scale model of short wind-generated waves and scatterometry. Journal of Geophysical Research: Oceans, 91(C9): 10735–10749. doi: 10.1029/JC091iC09p10735
[26]	Plant W J. 2002. A stochastic, multiscale model of microwave backscatter from the ocean. Journal of Geophysical Research, 107(C9): 3120. doi: 10.1029/2001JC000909
[27]	Plant W J, Irisov V. 2017. A joint active/passive physical model of sea surface microwave signatures. Journal of Geophysical Research: Oceans, 122(4): 3219–3239. doi: 10.1002/2017JC012749
[28]	Romeiser R, Alpers W, Wismann V. 1997. An improved composite surface model for the radar backscattering cross section of the ocean surface: 1. Theory of the model and optimization/validation by scatterometer data. Journal of Geophysical Research: Oceans, 102(C11): 25237–25250. doi: 10.1029/97JC00190
[29]	Shao Weizeng, Ding Yingying, Li Jichao, et al. 2019. Wave retrieval under typhoon conditions using a machine learning method applied to Gaofen-3 SAR imagery. Canadian Journal of Remote Sensing, 45(6): 723–732. doi: 10.1080/07038992.2019.1683444
[30]	Shao Weizeng, Sheng Yexin, Sun Jian. 2017. Preliminary assessment of wind and wave retrieval from Chinese Gaofen-3 SAR imagery. Sensors, 17(8): 1705. doi: 10.3390/s17081705
[31]	Stopa J E, Mouche A A, Chapron B, et al. 2017. Sea state impacts on wind speed retrievals from C-Band radars. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(5): 2147–2155. doi: 10.1109/JSTARS.2016.2609101
[32]	Voronovich A. 1994. Small-slope approximation for electromagnetic wave scattering at a rough interface of two dielectric half-spaces. Waves in Random Media, 4(3): 337–367. doi: 10.1088/0959-7174/4/3/008
[33]	Voronovich A G, Zavorotny V U. 2001. Theoretical model for scattering of radar signals in Ku- and C-bands from a rough sea surface with breaking waves. Waves in Random Media, 11(3): 247–269
[34]	Voronovich A G, Zavorotny V U. 2011. Depolarization of microwave backscattering from a rough sea surface: Modeling with small-slope approximation. In: Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium. Vancouver, BC: IEEE, 2033–2036
[35]	Wang He, Li Huimin, Lin Mingsen, et al. 2019. Calibration of the copolarized backscattering measurements from Gaofen-3 synthetic aperture radar wave mode imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(6): 1748–1762. doi: 10.1109/JSTARS.2019.2911922
[36]	Wang He, Yang Jingsong, Zhu Jianhua, et al. 2021. Estimation of significant wave heights from ASCAT scatterometer data via deep learning network. Remote Sensing, 13(2): 195. doi: 10.3390/rs13020195
[37]	Wu S T, Fung A K. 1972. A noncoherent model for microwave emissions and backscattering from the sea surface. Journal of Geophysical Research, 77(30): 5917–5929. doi: 10.1029/JC077i030p05917
[38]	Yan Qiushuang, Zhang Jie, Fan Chenqing, et al. 2018. Study of sea-surface slope distribution and its effect on radar backscatter based on Global Precipitation Measurement Ku-band precipitation radar measurements. Journal of Applied Remote Sensing, 12(1): 016006
[39]	Zhang Tianyu, Li Xiaoming, Feng Qian, et al. 2019. Retrieval of sea surface wind speeds from Gaofen-3 full polarimetric data. Remote Sensing, 11(7): 813. doi: 10.3390/rs11070813
[40]	Zhang Biao, Zhao Xiaolu, Perrie W, et al. 2020. On modeling of quad-polarization radar scattering from the ocean surface with breaking waves. Journal of Geophysical Research: Oceans, 125(8): e2020JC016319
[41]	Zhong Lihua, Qiu Xiaolan, Han Bing, et al. 2020. An improved descalloping method combined with imaging parameters for GaoFen-3 ScanSAR. Remote Sensing, 12(5): 822. doi: 10.3390/rs12050822